The Efficacy of Loackdown in New Zealand

I thought that I write another short essay on COVID-19 to analyze the effectiveness of the lockdown - the so called social distancing.

The idea of social distancing is perfectly logical. The virus is like a fire and people are like the wood, if people separate the fire dies down with minimum losses.

To model the infection rate I use the Gompertz Curve     https://en.wikipedia.org/wiki/Gompertz_function

You can look it up. It is a Sigmoid function which has four parameters, (a), (e), (b), and (c). The parameter (a) is an asymptote, (e) is called the Euler's constant equal to 2.71828, (b) is a parameter that governs the displacement along the x-axis, and (c) is the growth rate.

I take the data of the total infection cases in NZ from the World Health Organization (daily) Situation Report from the data we started reporting, which was Feb 28 up to Mar 27 to illustrate the fit of the data to the Gompertz Curve. For (a=0.1), (b=0.2) and (c=0.5) along with (e) fixed at 2.71828, the data seem to fit remarkably well.

Then I have two scenarios. The first scenario is about an effective and enforced lockdown, i.e. an effective social distancing. Under such scenario, the infection growth rate (c) falls significantly, and sooner. The second scenario is a less effective lockdown, whereby the growth rate falls at a slower rate and takes more time. Here are the assumed growth rate scenarios.

Here is the projection of the infection rate under the effective lockdown scenario. The infection rate peaks at 2,630 cases on April 3, then takes a nosedive very similar to the Chinese case.

And here is the less effective lockdown (less effective social distancing), where the infection peaks at a staggering 78,203 cases on April 15.

This is quite a significant increase in two weeks period, a staggering 75,573 more cases. It emphasizes the importance and effectiveness of the lockdown and strict social distancing, which seems to be crucial to defeat the virus. 

See Greenstone and Nigam (2020).[1] In a rather more elaborate model, they projected that moderate social distancing would save 1.7 million lives between March 1 and October 1 in the United States. 

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[1] Greenstone, M. and V. Nigam. (2020). Does Social Distancing Matter? University of Chicago - Becker Friedman Institute for Economics WP No. 2020-26

   

The Pandemic and Policy in New Zealand

The economic lessons of the COVID 19 pandemic are clear now. The economy is about people who produce goods and services then sell them in markets, i.e., global trade. Without labor, production declines regardless of how much capital is there.

Global growth will soon decline because of a decline in aggregate supply. Declining demand will make the situation worse. Those who claim that high growth is unnecessary or damaging will have to wake up and re-examine their claim. When economies stop growing life becomes very difficult.

The problem the world is facing now is not about throwing money at people. Money and credit have nothing to do with growth. It is about getting the production of goods and services to presume as soon as possible, trade to continue, and global markets to function. It is about labor now. The longer the pandemic lasts the more difficult the problem becomes. Although loose monetary and fiscal policies are typical response in such circumstances, health policy is most important. It is about managing the pandemic, and it is about making sure that the workforce remains healthy.

The PM realizes that the problem is about people first. Closing the border is the right decision. Responsible private institutions could suspend work, gatherings, parties, games, etc. without government instructions. Nonetheless, the economy will suffer especially if the pandemic takes longer to control and NZ winter catches up with it.      

My current research is about the effect of OCR on bank lending rate in New Zealand. The paper is work-in-progress, but here is what we found so far. My coauthor and I model a profit-maximizing representative NZ bank subject to a capital-asset ratio, and estimate the model. We make baseline projections to 2024 and examine additional projections under a number of counterfactual scenarios. The counterfactual scenarios include an OCR cut to 0.50, 0.25 (which is today’s announcement), zero, then –0.25 and –0.50. Everything else remains unchanged; the bank lending rate tumbles and eventually goes negative when the OCR is negative. Banks have to generate additional revenues, or reduce cost in order to keep profit unchanged; otherwise, profit will decline sharply and some banks may suffer substantial losses. It is important that we do not create the conditions for a banking crisis.